cosmodev ~/tools/cache-savings-calculator

Prompt tokens / request

Output tokens / request

Cache hits

Model

Prompt-caching savings

Saves $0.33 (43.33%)
$0.75 uncached → $0.43 cached · 5 requests
Break-even: 13 cache hits — reads must repay one write premium

The math

uncached = hits × (prompt×in$/M + output×out$/M) / 1M
          = 5 × (10,000×$10 + 1,000×$50) / 1M = $0.75
cached = (prompt×write$/M + hits × (prompt×read$/M + output×out$/M)) / 1M
       = (10,000×$12.5 + 5 × (10,000×$1 + 1,000×$50)) / 1M = $0.43
break-even hits = ceil(write$/M / read$/M) = ceil($12.5 / $1) = 13

Data as of 2026-09-27T12:03:11.094Z

cosmodev ~/docs/cache-savings-calculator.md

What it does

The Cache Savings Calculator shows what prompt caching actually saves on a repeated workload. Enter your prompt and output token counts plus how many requests reuse the cached prompt, pick a model, and it compares the uncached bill against the cached one — including the honest case where caching costs more.

The key nuance it captures is the write premium: the first request pays extra to store the prompt, and every later hit pays a much cheaper cache-read rate instead of full input price. The break-even figure tells you how many hits it takes for the cheap reads to repay that one write.

How to use it

Set Prompt tokens / request, Output tokens / request, and Cache hits with the steppers.
Pick a Model — cache-priced models sort first; models without published cache rates are marked “no cache rates” and show the explanatory empty state.
Read the headline: green when caching saves money, red when it costs more (too few hits to amortize the write).
Check The math block — both formulas rendered with your model’s live rates and your numbers substituted in.
Copy savings or Copy share link to send the exact scenario.

Examples

A repeated 10k-token prompt (5 hits)

Input: 10,000 prompt tokens, 1,000 output tokens, 5 cache hits, at $10/M input, $50/M output, $1/M cache read, $12.5/M cache write:

uncached = 5 × (10,000×$10 + 1,000×$50) / 1M = $0.75
cached   = (10,000×$12.5 + 5 × (10,000×$1 + 1,000×$50)) / 1M = $0.425
savings  = $0.325 (43.33%) · break-even = ceil(12.5 / 1) = 13 hits

A single request — caching loses

Same shape, 1 cache hit:

uncached = $0.15 · cached = $0.185 · savings = −$0.035

One hit never amortizes the write premium; the tool shows the negative result in an error tone rather than hiding it.

Good to know

Break-even counts reads, not requests. ceil(write$/M ÷ read$/M) is how many cache hits it takes for cumulative read spend to equal one write premium — below it, caching costs more.
Rates are a snapshot. Every figure flows from one dated model snapshot — check the “Data as of” line for freshness; models without published cache rates return no result instead of partial math.
Private: everything runs 100% client-side — no token counts or rates leave your browser.
Related tools: LLM Cost Calculator, Token Estimator, Embedding Chunk Planner.